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Researchers from the UK demonstrate the efficacy of self-supervised learning for human activity recognition using a vast wearable dataset. By addressing convergence issues and evaluating multi-task self-supervision, they showcase robust models with superior representation quality across diverse populations and activity types.
The research suggests that AI shows strong potential in future applications for addressing mental health and wellbeing.
Researchers are using artificial intelligence (AI) to detect behavioural signs of anxiety with more than 90 per cent accuracy, and suggest that AI could
Embedding Artificial Intelligence onto low-power devices is a challenging task that has been partly overcome with recent advances in machine learning and hardware design. Presently, deep neural networks can be deployed on embedded targets to perform different tasks such as speech recognition, object detection or Human Activity Recognition. However, there is still room for optimization of deep neural networks onto embedded devices. These optimizations mainly address power consumption, memory and real-time constraints, but also an easier deployment at the edge. Moreover, there is still a need fo...
A Multifaceted Enigma: Debaprasad Badajena SHARE e quintessence of a campus personality. Holding myriads of responsibilities such as the Convenor of Innovision-2019, Secretary at DBA Hall of Residence and representing the institute at various competitions, his work ethics made him a rare gem and a perfect role model for all those who admire him. Debaprasad has interned at the prestigious ISI Kolkata, American Express and finally, has bagged a coveted job at TATA Digital. Team MM met with Debaprasad Badajena over an online video call along with his close companions and discussed his voy...